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// This file was autogenerated by the `uniffi-bindgen-gecko-js` crate.
// Trust me, you don't want to mess with it!
import {
ArrayBufferDataStream,
FfiConverter,
FfiConverterArrayBuffer,
FfiConverterInt8,
FfiConverterUInt8,
FfiConverterInt16,
FfiConverterUInt16,
FfiConverterInt32,
FfiConverterUInt32,
FfiConverterInt64,
FfiConverterUInt64,
FfiConverterFloat32,
FfiConverterFloat64,
FfiConverterBoolean,
FfiConverterBytes,
FfiConverterString,
UniFFICallbackHandler,
UniFFICallbackMethodHandler,
UniFFIError,
UniFFIInternalError,
UniFFITypeError,
constructUniffiObject,
handleRustResult,
uniffiObjectPtr,
} from "moz-src:///toolkit/components/uniffi-js/js/UniFFI.sys.mjs";
// Objects intended to be used in the unit tests
export var UnitTestObjs = {
uniffiObjectPtr,
};
/**
* Calculate score for a piece of categorized content based on a user interest vector.
*
* This scoring function is of the following properties:
* - The score ranges from 0.0 to 1.0
* - The score is monotonically increasing for the accumulated interest count
*
* # Params:
* - `interest_vector`: a user interest vector that can be fetched via
* `RelevancyStore::user_interest_vector()`.
* - `content_categories`: a list of categories (interests) of the give content.
* # Return:
* - A score ranges in [0, 1].
* @param {InterestVector} interestVector
* @param {Array.<Interest>} contentCategories
* @returns {number}
*/
export function score(
interestVector,
contentCategories) {
FfiConverterTypeInterestVector.checkType(interestVector);
FfiConverterSequenceTypeInterest.checkType(contentCategories);
const result = UniFFIScaffolding.callSync(
9, // uniffi_relevancy_fn_func_score
FfiConverterTypeInterestVector.lower(interestVector),
FfiConverterSequenceTypeInterest.lower(contentCategories),
)
return handleRustResult(
result,
FfiConverterFloat64.lift.bind(FfiConverterFloat64),
null,
)
}
/**
* BanditData
*/
export class BanditData {
constructor(
{
bandit,
arm,
impressions,
clicks,
alpha,
beta
} = {
bandit: undefined,
arm: undefined,
impressions: undefined,
clicks: undefined,
alpha: undefined,
beta: undefined
}
) {
try {
FfiConverterString.checkType(bandit)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("bandit");
}
throw e;
}
try {
FfiConverterString.checkType(arm)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("arm");
}
throw e;
}
try {
FfiConverterUInt64.checkType(impressions)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("impressions");
}
throw e;
}
try {
FfiConverterUInt64.checkType(clicks)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("clicks");
}
throw e;
}
try {
FfiConverterUInt64.checkType(alpha)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("alpha");
}
throw e;
}
try {
FfiConverterUInt64.checkType(beta)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("beta");
}
throw e;
}
/**
* bandit
*/
this.bandit = bandit;
/**
* arm
*/
this.arm = arm;
/**
* impressions
*/
this.impressions = impressions;
/**
* clicks
*/
this.clicks = clicks;
/**
* alpha
*/
this.alpha = alpha;
/**
* beta
*/
this.beta = beta;
}
equals(other) {
return (
this.bandit == other.bandit
&& this.arm == other.arm
&& this.impressions == other.impressions
&& this.clicks == other.clicks
&& this.alpha == other.alpha
&& this.beta == other.beta
)
}
}
// Export the FFIConverter object to make external types work.
export class FfiConverterTypeBanditData extends FfiConverterArrayBuffer {
static read(dataStream) {
return new BanditData({
bandit: FfiConverterString.read(dataStream),
arm: FfiConverterString.read(dataStream),
impressions: FfiConverterUInt64.read(dataStream),
clicks: FfiConverterUInt64.read(dataStream),
alpha: FfiConverterUInt64.read(dataStream),
beta: FfiConverterUInt64.read(dataStream),
});
}
static write(dataStream, value) {
FfiConverterString.write(dataStream, value.bandit);
FfiConverterString.write(dataStream, value.arm);
FfiConverterUInt64.write(dataStream, value.impressions);
FfiConverterUInt64.write(dataStream, value.clicks);
FfiConverterUInt64.write(dataStream, value.alpha);
FfiConverterUInt64.write(dataStream, value.beta);
}
static computeSize(value) {
let totalSize = 0;
totalSize += FfiConverterString.computeSize(value.bandit);
totalSize += FfiConverterString.computeSize(value.arm);
totalSize += FfiConverterUInt64.computeSize(value.impressions);
totalSize += FfiConverterUInt64.computeSize(value.clicks);
totalSize += FfiConverterUInt64.computeSize(value.alpha);
totalSize += FfiConverterUInt64.computeSize(value.beta);
return totalSize
}
static checkType(value) {
super.checkType(value);
if (!(value instanceof BanditData)) {
throw new UniFFITypeError(`Expected 'BanditData', found '${typeof value}'`);
}
try {
FfiConverterString.checkType(value.bandit);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".bandit");
}
throw e;
}
try {
FfiConverterString.checkType(value.arm);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".arm");
}
throw e;
}
try {
FfiConverterUInt64.checkType(value.impressions);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".impressions");
}
throw e;
}
try {
FfiConverterUInt64.checkType(value.clicks);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".clicks");
}
throw e;
}
try {
FfiConverterUInt64.checkType(value.alpha);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".alpha");
}
throw e;
}
try {
FfiConverterUInt64.checkType(value.beta);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".beta");
}
throw e;
}
}
}
/**
* Interest metrics that we want to send to Glean as part of the validation process. These contain
* the cosine similarity when comparing the user's interest against various interest vectors that
* consumers may use.
*
* Cosine similarly was chosen because it seems easy to calculate. This was then matched against
* some semi-plausible real-world interest vectors that consumers might use. This is all up for
* debate and we may decide to switch to some other metrics.
*
* Similarity values are transformed to integers by multiplying the floating point value by 1000 and
* rounding. This is to make them compatible with Glean's distribution metrics.
*/
export class InterestMetrics {
constructor(
{
topSingleInterestSimilarity,
top2interestSimilarity,
top3interestSimilarity
} = {
topSingleInterestSimilarity: undefined,
top2interestSimilarity: undefined,
top3interestSimilarity: undefined
}
) {
try {
FfiConverterUInt32.checkType(topSingleInterestSimilarity)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("topSingleInterestSimilarity");
}
throw e;
}
try {
FfiConverterUInt32.checkType(top2interestSimilarity)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("top2interestSimilarity");
}
throw e;
}
try {
FfiConverterUInt32.checkType(top3interestSimilarity)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("top3interestSimilarity");
}
throw e;
}
/**
* Similarity between the user's interest vector and an interest vector where the element for
* the user's top interest is copied, but all other interests are set to zero. This measures
* the highest possible similarity with consumers that used interest vectors with a single
* interest set.
*/
this.topSingleInterestSimilarity = topSingleInterestSimilarity;
/**
* The same as before, but the top 2 interests are copied. This measures the highest possible
* similarity with consumers that used interest vectors with a two interests (note: this means
* they would need to choose the user's top two interests and have the exact same proportion
* between them as the user).
*/
this.top2interestSimilarity = top2interestSimilarity;
/**
* The same as before, but the top 3 interests are copied.
*/
this.top3interestSimilarity = top3interestSimilarity;
}
equals(other) {
return (
this.topSingleInterestSimilarity == other.topSingleInterestSimilarity
&& this.top2interestSimilarity == other.top2interestSimilarity
&& this.top3interestSimilarity == other.top3interestSimilarity
)
}
}
// Export the FFIConverter object to make external types work.
export class FfiConverterTypeInterestMetrics extends FfiConverterArrayBuffer {
static read(dataStream) {
return new InterestMetrics({
topSingleInterestSimilarity: FfiConverterUInt32.read(dataStream),
top2interestSimilarity: FfiConverterUInt32.read(dataStream),
top3interestSimilarity: FfiConverterUInt32.read(dataStream),
});
}
static write(dataStream, value) {
FfiConverterUInt32.write(dataStream, value.topSingleInterestSimilarity);
FfiConverterUInt32.write(dataStream, value.top2interestSimilarity);
FfiConverterUInt32.write(dataStream, value.top3interestSimilarity);
}
static computeSize(value) {
let totalSize = 0;
totalSize += FfiConverterUInt32.computeSize(value.topSingleInterestSimilarity);
totalSize += FfiConverterUInt32.computeSize(value.top2interestSimilarity);
totalSize += FfiConverterUInt32.computeSize(value.top3interestSimilarity);
return totalSize
}
static checkType(value) {
super.checkType(value);
if (!(value instanceof InterestMetrics)) {
throw new UniFFITypeError(`Expected 'InterestMetrics', found '${typeof value}'`);
}
try {
FfiConverterUInt32.checkType(value.topSingleInterestSimilarity);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".topSingleInterestSimilarity");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.top2interestSimilarity);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".top2interestSimilarity");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.top3interestSimilarity);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".top3interestSimilarity");
}
throw e;
}
}
}
/**
* Vector storing a count value for each interest
*
* Here "vector" refers to the mathematical object, not a Rust `Vec`. It always has a fixed
* number of elements.
*/
export class InterestVector {
constructor(
{
inconclusive,
animals,
arts,
autos,
business,
career,
education,
fashion,
finance,
food,
government,
hobbies,
home,
news,
realEstate,
society,
sports,
tech,
travel
} = {
inconclusive: undefined,
animals: undefined,
arts: undefined,
autos: undefined,
business: undefined,
career: undefined,
education: undefined,
fashion: undefined,
finance: undefined,
food: undefined,
government: undefined,
hobbies: undefined,
home: undefined,
news: undefined,
realEstate: undefined,
society: undefined,
sports: undefined,
tech: undefined,
travel: undefined
}
) {
try {
FfiConverterUInt32.checkType(inconclusive)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("inconclusive");
}
throw e;
}
try {
FfiConverterUInt32.checkType(animals)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("animals");
}
throw e;
}
try {
FfiConverterUInt32.checkType(arts)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("arts");
}
throw e;
}
try {
FfiConverterUInt32.checkType(autos)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("autos");
}
throw e;
}
try {
FfiConverterUInt32.checkType(business)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("business");
}
throw e;
}
try {
FfiConverterUInt32.checkType(career)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("career");
}
throw e;
}
try {
FfiConverterUInt32.checkType(education)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("education");
}
throw e;
}
try {
FfiConverterUInt32.checkType(fashion)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("fashion");
}
throw e;
}
try {
FfiConverterUInt32.checkType(finance)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("finance");
}
throw e;
}
try {
FfiConverterUInt32.checkType(food)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("food");
}
throw e;
}
try {
FfiConverterUInt32.checkType(government)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("government");
}
throw e;
}
try {
FfiConverterUInt32.checkType(hobbies)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("hobbies");
}
throw e;
}
try {
FfiConverterUInt32.checkType(home)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("home");
}
throw e;
}
try {
FfiConverterUInt32.checkType(news)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("news");
}
throw e;
}
try {
FfiConverterUInt32.checkType(realEstate)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("realEstate");
}
throw e;
}
try {
FfiConverterUInt32.checkType(society)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("society");
}
throw e;
}
try {
FfiConverterUInt32.checkType(sports)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("sports");
}
throw e;
}
try {
FfiConverterUInt32.checkType(tech)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("tech");
}
throw e;
}
try {
FfiConverterUInt32.checkType(travel)
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart("travel");
}
throw e;
}
/**
* inconclusive
*/
this.inconclusive = inconclusive;
/**
* animals
*/
this.animals = animals;
/**
* arts
*/
this.arts = arts;
/**
* autos
*/
this.autos = autos;
/**
* business
*/
this.business = business;
/**
* career
*/
this.career = career;
/**
* education
*/
this.education = education;
/**
* fashion
*/
this.fashion = fashion;
/**
* finance
*/
this.finance = finance;
/**
* food
*/
this.food = food;
/**
* government
*/
this.government = government;
/**
* hobbies
*/
this.hobbies = hobbies;
/**
* home
*/
this.home = home;
/**
* news
*/
this.news = news;
/**
* realEstate
*/
this.realEstate = realEstate;
/**
* society
*/
this.society = society;
/**
* sports
*/
this.sports = sports;
/**
* tech
*/
this.tech = tech;
/**
* travel
*/
this.travel = travel;
}
equals(other) {
return (
this.inconclusive == other.inconclusive
&& this.animals == other.animals
&& this.arts == other.arts
&& this.autos == other.autos
&& this.business == other.business
&& this.career == other.career
&& this.education == other.education
&& this.fashion == other.fashion
&& this.finance == other.finance
&& this.food == other.food
&& this.government == other.government
&& this.hobbies == other.hobbies
&& this.home == other.home
&& this.news == other.news
&& this.realEstate == other.realEstate
&& this.society == other.society
&& this.sports == other.sports
&& this.tech == other.tech
&& this.travel == other.travel
)
}
}
// Export the FFIConverter object to make external types work.
export class FfiConverterTypeInterestVector extends FfiConverterArrayBuffer {
static read(dataStream) {
return new InterestVector({
inconclusive: FfiConverterUInt32.read(dataStream),
animals: FfiConverterUInt32.read(dataStream),
arts: FfiConverterUInt32.read(dataStream),
autos: FfiConverterUInt32.read(dataStream),
business: FfiConverterUInt32.read(dataStream),
career: FfiConverterUInt32.read(dataStream),
education: FfiConverterUInt32.read(dataStream),
fashion: FfiConverterUInt32.read(dataStream),
finance: FfiConverterUInt32.read(dataStream),
food: FfiConverterUInt32.read(dataStream),
government: FfiConverterUInt32.read(dataStream),
hobbies: FfiConverterUInt32.read(dataStream),
home: FfiConverterUInt32.read(dataStream),
news: FfiConverterUInt32.read(dataStream),
realEstate: FfiConverterUInt32.read(dataStream),
society: FfiConverterUInt32.read(dataStream),
sports: FfiConverterUInt32.read(dataStream),
tech: FfiConverterUInt32.read(dataStream),
travel: FfiConverterUInt32.read(dataStream),
});
}
static write(dataStream, value) {
FfiConverterUInt32.write(dataStream, value.inconclusive);
FfiConverterUInt32.write(dataStream, value.animals);
FfiConverterUInt32.write(dataStream, value.arts);
FfiConverterUInt32.write(dataStream, value.autos);
FfiConverterUInt32.write(dataStream, value.business);
FfiConverterUInt32.write(dataStream, value.career);
FfiConverterUInt32.write(dataStream, value.education);
FfiConverterUInt32.write(dataStream, value.fashion);
FfiConverterUInt32.write(dataStream, value.finance);
FfiConverterUInt32.write(dataStream, value.food);
FfiConverterUInt32.write(dataStream, value.government);
FfiConverterUInt32.write(dataStream, value.hobbies);
FfiConverterUInt32.write(dataStream, value.home);
FfiConverterUInt32.write(dataStream, value.news);
FfiConverterUInt32.write(dataStream, value.realEstate);
FfiConverterUInt32.write(dataStream, value.society);
FfiConverterUInt32.write(dataStream, value.sports);
FfiConverterUInt32.write(dataStream, value.tech);
FfiConverterUInt32.write(dataStream, value.travel);
}
static computeSize(value) {
let totalSize = 0;
totalSize += FfiConverterUInt32.computeSize(value.inconclusive);
totalSize += FfiConverterUInt32.computeSize(value.animals);
totalSize += FfiConverterUInt32.computeSize(value.arts);
totalSize += FfiConverterUInt32.computeSize(value.autos);
totalSize += FfiConverterUInt32.computeSize(value.business);
totalSize += FfiConverterUInt32.computeSize(value.career);
totalSize += FfiConverterUInt32.computeSize(value.education);
totalSize += FfiConverterUInt32.computeSize(value.fashion);
totalSize += FfiConverterUInt32.computeSize(value.finance);
totalSize += FfiConverterUInt32.computeSize(value.food);
totalSize += FfiConverterUInt32.computeSize(value.government);
totalSize += FfiConverterUInt32.computeSize(value.hobbies);
totalSize += FfiConverterUInt32.computeSize(value.home);
totalSize += FfiConverterUInt32.computeSize(value.news);
totalSize += FfiConverterUInt32.computeSize(value.realEstate);
totalSize += FfiConverterUInt32.computeSize(value.society);
totalSize += FfiConverterUInt32.computeSize(value.sports);
totalSize += FfiConverterUInt32.computeSize(value.tech);
totalSize += FfiConverterUInt32.computeSize(value.travel);
return totalSize
}
static checkType(value) {
super.checkType(value);
if (!(value instanceof InterestVector)) {
throw new UniFFITypeError(`Expected 'InterestVector', found '${typeof value}'`);
}
try {
FfiConverterUInt32.checkType(value.inconclusive);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".inconclusive");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.animals);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".animals");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.arts);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".arts");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.autos);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".autos");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.business);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".business");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.career);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".career");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.education);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".education");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.fashion);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".fashion");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.finance);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".finance");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.food);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".food");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.government);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".government");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.hobbies);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".hobbies");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.home);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".home");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.news);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".news");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.realEstate);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".realEstate");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.society);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".society");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.sports);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".sports");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.tech);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".tech");
}
throw e;
}
try {
FfiConverterUInt32.checkType(value.travel);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(".travel");
}
throw e;
}
}
}
/**
* List of possible interests for a domain. Domains can have be associated with one or multiple
* interests. `Inconclusive` is used for domains in the user's top sites that we can't classify
* because there's no corresponding entry in the interest database.
*/
export const Interest = {
/**
* INCONCLUSIVE
*/
INCONCLUSIVE: 0,
/**
* ANIMALS
*/
ANIMALS: 1,
/**
* ARTS
*/
ARTS: 2,
/**
* AUTOS
*/
AUTOS: 3,
/**
* BUSINESS
*/
BUSINESS: 4,
/**
* CAREER
*/
CAREER: 5,
/**
* EDUCATION
*/
EDUCATION: 6,
/**
* FASHION
*/
FASHION: 7,
/**
* FINANCE
*/
FINANCE: 8,
/**
* FOOD
*/
FOOD: 9,
/**
* GOVERNMENT
*/
GOVERNMENT: 10,
/**
* HOBBIES
*/
HOBBIES: 12,
/**
* HOME
*/
HOME: 13,
/**
* NEWS
*/
NEWS: 14,
/**
* REAL_ESTATE
*/
REAL_ESTATE: 15,
/**
* SOCIETY
*/
SOCIETY: 16,
/**
* SPORTS
*/
SPORTS: 17,
/**
* TECH
*/
TECH: 18,
/**
* TRAVEL
*/
TRAVEL: 19,
};
Object.freeze(Interest);
// Export the FFIConverter object to make external types work.
export class FfiConverterTypeInterest extends FfiConverterArrayBuffer {
static #validValues = Object.values(Interest)
static read(dataStream) {
// Use sequential indices (1-based) for the wire format to match the Rust scaffolding
switch (dataStream.readInt32()) {
case 1:
return Interest.INCONCLUSIVE
case 2:
return Interest.ANIMALS
case 3:
return Interest.ARTS
case 4:
return Interest.AUTOS
case 5:
return Interest.BUSINESS
case 6:
return Interest.CAREER
case 7:
return Interest.EDUCATION
case 8:
return Interest.FASHION
case 9:
return Interest.FINANCE
case 10:
return Interest.FOOD
case 11:
return Interest.GOVERNMENT
case 12:
return Interest.HOBBIES
case 13:
return Interest.HOME
case 14:
return Interest.NEWS
case 15:
return Interest.REAL_ESTATE
case 16:
return Interest.SOCIETY
case 17:
return Interest.SPORTS
case 18:
return Interest.TECH
case 19:
return Interest.TRAVEL
default:
throw new UniFFITypeError("Unknown Interest variant");
}
}
static write(dataStream, value) {
// Use sequential indices (1-based) for the wire format to match the Rust scaffolding
if (value === Interest.INCONCLUSIVE) {
dataStream.writeInt32(1);
return;
}
if (value === Interest.ANIMALS) {
dataStream.writeInt32(2);
return;
}
if (value === Interest.ARTS) {
dataStream.writeInt32(3);
return;
}
if (value === Interest.AUTOS) {
dataStream.writeInt32(4);
return;
}
if (value === Interest.BUSINESS) {
dataStream.writeInt32(5);
return;
}
if (value === Interest.CAREER) {
dataStream.writeInt32(6);
return;
}
if (value === Interest.EDUCATION) {
dataStream.writeInt32(7);
return;
}
if (value === Interest.FASHION) {
dataStream.writeInt32(8);
return;
}
if (value === Interest.FINANCE) {
dataStream.writeInt32(9);
return;
}
if (value === Interest.FOOD) {
dataStream.writeInt32(10);
return;
}
if (value === Interest.GOVERNMENT) {
dataStream.writeInt32(11);
return;
}
if (value === Interest.HOBBIES) {
dataStream.writeInt32(12);
return;
}
if (value === Interest.HOME) {
dataStream.writeInt32(13);
return;
}
if (value === Interest.NEWS) {
dataStream.writeInt32(14);
return;
}
if (value === Interest.REAL_ESTATE) {
dataStream.writeInt32(15);
return;
}
if (value === Interest.SOCIETY) {
dataStream.writeInt32(16);
return;
}
if (value === Interest.SPORTS) {
dataStream.writeInt32(17);
return;
}
if (value === Interest.TECH) {
dataStream.writeInt32(18);
return;
}
if (value === Interest.TRAVEL) {
dataStream.writeInt32(19);
return;
}
throw new UniFFITypeError("Unknown Interest variant");
}
static computeSize(value) {
return 4;
}
static checkType(value) {
// Check that the value is a valid enum variant
if (!this.#validValues.includes(value)) {
throw new UniFFITypeError(`${value} is not a valid value for Interest`);
}
}
}
/**
* Errors we return via the public interface.
*/
export class RelevancyApiError extends Error {}
/**
* Unexpected
*/
export class Unexpected extends RelevancyApiError {
constructor(
reason,
...params
) {
const message = `reason: ${ reason }`;
super(message, ...params);
this.reason = reason;
}
toString() {
return `Unexpected: ${super.toString()}`
}
}
// Export the FFIConverter object to make external types work.
export class FfiConverterTypeRelevancyApiError extends FfiConverterArrayBuffer {
static read(dataStream) {
switch (dataStream.readInt32()) {
case 1:
return new Unexpected(
FfiConverterString.read(dataStream)
);
default:
throw new UniFFITypeError("Unknown RelevancyApiError variant");
}
}
static computeSize(value) {
// Size of the Int indicating the variant
let totalSize = 4;
if (value instanceof Unexpected) {
totalSize += FfiConverterString.computeSize(value.reason);
return totalSize;
}
throw new UniFFITypeError("Unknown RelevancyApiError variant");
}
static write(dataStream, value) {
if (value instanceof Unexpected) {
dataStream.writeInt32(1);
FfiConverterString.write(dataStream, value.reason);
return;
}
throw new UniFFITypeError("Unknown RelevancyApiError variant");
}
static errorClass = RelevancyApiError;
}
// Export the FFIConverter object to make external types work.
export class FfiConverterSequenceString extends FfiConverterArrayBuffer {
static read(dataStream) {
const len = dataStream.readInt32();
const arr = [];
for (let i = 0; i < len; i++) {
arr.push(FfiConverterString.read(dataStream));
}
return arr;
}
static write(dataStream, value) {
dataStream.writeInt32(value.length);
value.forEach((innerValue) => {
FfiConverterString.write(dataStream, innerValue);
})
}
static computeSize(value) {
// The size of the length
let size = 4;
for (const innerValue of value) {
size += FfiConverterString.computeSize(innerValue);
}
return size;
}
static checkType(value) {
if (!Array.isArray(value)) {
throw new UniFFITypeError(`${value} is not an array`);
}
value.forEach((innerValue, idx) => {
try {
FfiConverterString.checkType(innerValue);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(`[${idx}]`);
}
throw e;
}
})
}
}
/**
* RelevancyStoreInterface
*/
export class RelevancyStoreInterface {
/**
* Initializes probability distributions for any uninitialized items (arms) within a bandit model.
*
* This method takes a `bandit` identifier and a list of `arms` (items) and ensures that each arm
* in the list has an initialized probability distribution in the database. For each arm, if the
* probability distribution does not already exist, it will be created, using Beta(1,1) as default,
* which represents uniform distribution.
* @param {string} bandit
* @param {Array.<string>} arms
*/
async banditInit(
bandit,
arms) {
throw Error("banditInit not implemented");
}
/**
* Selects the optimal item (arm) to display to the user based on a multi-armed bandit model.
*
* This method takes in a `bandit` identifier and a list of possible `arms` (items) and uses a
* Thompson sampling approach to select the arm with the highest probability of success.
* For each arm, it retrieves the Beta distribution parameters (alpha and beta) from the
* database, creates a Beta distribution, and samples from it to estimate the arm's probability
* of success. The arm with the highest sampled probability is selected and returned.
* @param {string} bandit
* @param {Array.<string>} arms
* @returns {Promise<string>}}
*/
async banditSelect(
bandit,
arms) {
throw Error("banditSelect not implemented");
}
/**
* Updates the bandit model's arm data based on user interaction (selection or non-selection).
*
* This method takes in a `bandit` identifier, an `arm` identifier, and a `selected` flag.
* If `selected` is true, it updates the model to reflect a successful selection of the arm,
* reinforcing its positive reward probability. If `selected` is false, it updates the
* beta (failure) distribution of the arm, reflecting a lack of selection and reinforcing
* its likelihood of a negative outcome.
* @param {string} bandit
* @param {string} arm
* @param {boolean} selected
*/
async banditUpdate(
bandit,
arm,
selected) {
throw Error("banditUpdate not implemented");
}
/**
* Close any open resources (for example databases)
*
* Calling `close` will interrupt any in-progress queries on other threads.
*/
close() {
throw Error("close not implemented");
}
/**
* Download the interest data from remote settings if needed
*/
async ensureInterestDataPopulated() {
throw Error("ensureInterestDataPopulated not implemented");
}
/**
* Retrieves the data for a specific bandit and arm.
* @param {string} bandit
* @param {string} arm
* @returns {Promise<BanditData>}}
*/
async getBanditData(
bandit,
arm) {
throw Error("getBanditData not implemented");
}
/**
* Ingest top URLs to build the user's interest vector.
*
* Consumer should pass a list of the user's top URLs by frecency to this method. It will
* then:
*
* - Download the URL interest data from remote settings. Eventually this should be cached /
* stored in the database, but for now it would be fine to download fresh data each time.
* - Match the user's top URls against the interest data to build up their interest vector.
* - Store the user's interest vector in the database.
*
* This method may execute for a long time and should only be called from a worker thread.
* @param {Array.<string>} topUrlsByFrecency
* @returns {Promise<InterestVector>}}
*/
async ingest(
topUrlsByFrecency) {
throw Error("ingest not implemented");
}
/**
* Interrupt any current database queries
*/
interrupt() {
throw Error("interrupt not implemented");
}
/**
* Get the user's interest vector directly.
*
* This runs after [Self::ingest]. It returns the interest vector directly so that the
* consumer can show it in an `about:` page.
* @returns {Promise<InterestVector>}}
*/
async userInterestVector() {
throw Error("userInterestVector not implemented");
}
}
/**
* RelevancyStore
*/
export class RelevancyStore extends RelevancyStoreInterface {
// Use `init` to instantiate this class.
// DO NOT USE THIS CONSTRUCTOR DIRECTLY
constructor(opts) {
super();
if (!Object.prototype.hasOwnProperty.call(opts, constructUniffiObject)) {
throw new UniFFIError("Attempting to construct an int using the JavaScript constructor directly" +
"Please use a UDL defined constructor, or the init function for the primary constructor")
}
if (!(opts[constructUniffiObject] instanceof UniFFIPointer)) {
throw new UniFFIError("Attempting to create a UniFFI object with a pointer that is not an instance of UniFFIPointer")
}
this[uniffiObjectPtr] = opts[constructUniffiObject];
}
/**
* Construct a new RelevancyStore
*
* This is non-blocking since databases and other resources are lazily opened.
* @param {string} dbPath
* @param {RemoteSettingsService} remoteSettings
* @returns {RelevancyStore}
*/
static init(
dbPath,
remoteSettings) {
FfiConverterString.checkType(dbPath);
FfiConverterTypeRemoteSettingsService.checkType(remoteSettings);
const result = UniFFIScaffolding.callSync(
10, // uniffi_relevancy_fn_constructor_relevancystore_new
FfiConverterString.lower(dbPath),
FfiConverterTypeRemoteSettingsService.lower(remoteSettings),
)
return handleRustResult(
result,
FfiConverterTypeRelevancyStore.lift.bind(FfiConverterTypeRelevancyStore),
null,
)
}
/**
* Initializes probability distributions for any uninitialized items (arms) within a bandit model.
*
* This method takes a `bandit` identifier and a list of `arms` (items) and ensures that each arm
* in the list has an initialized probability distribution in the database. For each arm, if the
* probability distribution does not already exist, it will be created, using Beta(1,1) as default,
* which represents uniform distribution.
* @param {string} bandit
* @param {Array.<string>} arms
*/
async banditInit(
bandit,
arms) {
FfiConverterString.checkType(bandit);
FfiConverterSequenceString.checkType(arms);
const result = await UniFFIScaffolding.callAsyncWrapper(
11, // uniffi_relevancy_fn_method_relevancystore_bandit_init
FfiConverterTypeRelevancyStore.lowerReceiver(this),
FfiConverterString.lower(bandit),
FfiConverterSequenceString.lower(arms),
)
return handleRustResult(
result,
(result) => undefined,
FfiConverterTypeRelevancyApiError.lift.bind(FfiConverterTypeRelevancyApiError),
)
}
/**
* Selects the optimal item (arm) to display to the user based on a multi-armed bandit model.
*
* This method takes in a `bandit` identifier and a list of possible `arms` (items) and uses a
* Thompson sampling approach to select the arm with the highest probability of success.
* For each arm, it retrieves the Beta distribution parameters (alpha and beta) from the
* database, creates a Beta distribution, and samples from it to estimate the arm's probability
* of success. The arm with the highest sampled probability is selected and returned.
* @param {string} bandit
* @param {Array.<string>} arms
* @returns {Promise<string>}}
*/
async banditSelect(
bandit,
arms) {
FfiConverterString.checkType(bandit);
FfiConverterSequenceString.checkType(arms);
const result = await UniFFIScaffolding.callAsyncWrapper(
12, // uniffi_relevancy_fn_method_relevancystore_bandit_select
FfiConverterTypeRelevancyStore.lowerReceiver(this),
FfiConverterString.lower(bandit),
FfiConverterSequenceString.lower(arms),
)
return handleRustResult(
result,
FfiConverterString.lift.bind(FfiConverterString),
FfiConverterTypeRelevancyApiError.lift.bind(FfiConverterTypeRelevancyApiError),
)
}
/**
* Updates the bandit model's arm data based on user interaction (selection or non-selection).
*
* This method takes in a `bandit` identifier, an `arm` identifier, and a `selected` flag.
* If `selected` is true, it updates the model to reflect a successful selection of the arm,
* reinforcing its positive reward probability. If `selected` is false, it updates the
* beta (failure) distribution of the arm, reflecting a lack of selection and reinforcing
* its likelihood of a negative outcome.
* @param {string} bandit
* @param {string} arm
* @param {boolean} selected
*/
async banditUpdate(
bandit,
arm,
selected) {
FfiConverterString.checkType(bandit);
FfiConverterString.checkType(arm);
FfiConverterBoolean.checkType(selected);
const result = await UniFFIScaffolding.callAsyncWrapper(
13, // uniffi_relevancy_fn_method_relevancystore_bandit_update
FfiConverterTypeRelevancyStore.lowerReceiver(this),
FfiConverterString.lower(bandit),
FfiConverterString.lower(arm),
FfiConverterBoolean.lower(selected),
)
return handleRustResult(
result,
(result) => undefined,
FfiConverterTypeRelevancyApiError.lift.bind(FfiConverterTypeRelevancyApiError),
)
}
/**
* Close any open resources (for example databases)
*
* Calling `close` will interrupt any in-progress queries on other threads.
*/
close() {
const result = UniFFIScaffolding.callSync(
14, // uniffi_relevancy_fn_method_relevancystore_close
FfiConverterTypeRelevancyStore.lowerReceiver(this),
)
return handleRustResult(
result,
(result) => undefined,
null,
)
}
/**
* Download the interest data from remote settings if needed
*/
async ensureInterestDataPopulated() {
const result = await UniFFIScaffolding.callAsyncWrapper(
15, // uniffi_relevancy_fn_method_relevancystore_ensure_interest_data_populated
FfiConverterTypeRelevancyStore.lowerReceiver(this),
)
return handleRustResult(
result,
(result) => undefined,
FfiConverterTypeRelevancyApiError.lift.bind(FfiConverterTypeRelevancyApiError),
)
}
/**
* Retrieves the data for a specific bandit and arm.
* @param {string} bandit
* @param {string} arm
* @returns {Promise<BanditData>}}
*/
async getBanditData(
bandit,
arm) {
FfiConverterString.checkType(bandit);
FfiConverterString.checkType(arm);
const result = await UniFFIScaffolding.callAsyncWrapper(
16, // uniffi_relevancy_fn_method_relevancystore_get_bandit_data
FfiConverterTypeRelevancyStore.lowerReceiver(this),
FfiConverterString.lower(bandit),
FfiConverterString.lower(arm),
)
return handleRustResult(
result,
FfiConverterTypeBanditData.lift.bind(FfiConverterTypeBanditData),
FfiConverterTypeRelevancyApiError.lift.bind(FfiConverterTypeRelevancyApiError),
)
}
/**
* Ingest top URLs to build the user's interest vector.
*
* Consumer should pass a list of the user's top URLs by frecency to this method. It will
* then:
*
* - Download the URL interest data from remote settings. Eventually this should be cached /
* stored in the database, but for now it would be fine to download fresh data each time.
* - Match the user's top URls against the interest data to build up their interest vector.
* - Store the user's interest vector in the database.
*
* This method may execute for a long time and should only be called from a worker thread.
* @param {Array.<string>} topUrlsByFrecency
* @returns {Promise<InterestVector>}}
*/
async ingest(
topUrlsByFrecency) {
FfiConverterSequenceString.checkType(topUrlsByFrecency);
const result = await UniFFIScaffolding.callAsyncWrapper(
17, // uniffi_relevancy_fn_method_relevancystore_ingest
FfiConverterTypeRelevancyStore.lowerReceiver(this),
FfiConverterSequenceString.lower(topUrlsByFrecency),
)
return handleRustResult(
result,
FfiConverterTypeInterestVector.lift.bind(FfiConverterTypeInterestVector),
FfiConverterTypeRelevancyApiError.lift.bind(FfiConverterTypeRelevancyApiError),
)
}
/**
* Interrupt any current database queries
*/
interrupt() {
const result = UniFFIScaffolding.callSync(
18, // uniffi_relevancy_fn_method_relevancystore_interrupt
FfiConverterTypeRelevancyStore.lowerReceiver(this),
)
return handleRustResult(
result,
(result) => undefined,
null,
)
}
/**
* Get the user's interest vector directly.
*
* This runs after [Self::ingest]. It returns the interest vector directly so that the
* consumer can show it in an `about:` page.
* @returns {Promise<InterestVector>}}
*/
async userInterestVector() {
const result = await UniFFIScaffolding.callAsyncWrapper(
19, // uniffi_relevancy_fn_method_relevancystore_user_interest_vector
FfiConverterTypeRelevancyStore.lowerReceiver(this),
)
return handleRustResult(
result,
FfiConverterTypeInterestVector.lift.bind(FfiConverterTypeInterestVector),
FfiConverterTypeRelevancyApiError.lift.bind(FfiConverterTypeRelevancyApiError),
)
}
}
// Export the FFIConverter object to make external types work.
export class FfiConverterTypeRelevancyStore extends FfiConverter {
static lift(value) {
const opts = {};
opts[constructUniffiObject] = value;
return new RelevancyStore(opts);
}
static lower(value) {
const ptr = value[uniffiObjectPtr];
if (!(ptr instanceof UniFFIPointer)) {
throw new UniFFITypeError("Object is not a 'RelevancyStore' instance");
}
return ptr;
}
static lowerReceiver(value) {
// This works exactly the same as lower for non-trait interfaces
return this.lower(value);
}
static read(dataStream) {
return this.lift(dataStream.readPointer(3));
}
static write(dataStream, value) {
dataStream.writePointer(3, this.lower(value));
}
static computeSize(value) {
return 8;
}
}
// Export the FFIConverter object to make external types work.
export class FfiConverterSequenceTypeInterest extends FfiConverterArrayBuffer {
static read(dataStream) {
const len = dataStream.readInt32();
const arr = [];
for (let i = 0; i < len; i++) {
arr.push(FfiConverterTypeInterest.read(dataStream));
}
return arr;
}
static write(dataStream, value) {
dataStream.writeInt32(value.length);
value.forEach((innerValue) => {
FfiConverterTypeInterest.write(dataStream, innerValue);
})
}
static computeSize(value) {
// The size of the length
let size = 4;
for (const innerValue of value) {
size += FfiConverterTypeInterest.computeSize(innerValue);
}
return size;
}
static checkType(value) {
if (!Array.isArray(value)) {
throw new UniFFITypeError(`${value} is not an array`);
}
value.forEach((innerValue, idx) => {
try {
FfiConverterTypeInterest.checkType(innerValue);
} catch (e) {
if (e instanceof UniFFITypeError) {
e.addItemDescriptionPart(`[${idx}]`);
}
throw e;
}
})
}
}
import {
FfiConverterTypeRemoteSettingsService,
} from "./RustRemoteSettings.sys.mjs";
// Export the FFIConverter object to make external types work.
export { FfiConverterTypeRemoteSettingsService };